In dataflow-oriented software systems separate components need to exchange information either by sending messages (payloads) through a communication channel or with direct calls. If it is restricted to message passing, payloads will encapsulate all kinds of information but components need a way to distinguish the type as well as other message attributes such as asynchronousity, priority... Some overhead is associated with every message transfer. Depending on the the kind of communication, the mechanism must be optimized.

Payloads give a solution to this problem. Payloads are self-identifying, dynamically typed objects such that the type of information can be easily identified. Payloads have two components: a descriptor component and a data component. In the case where different components are on different machines, payloads need to offer serialization in order to be transmitted over the channel.

Payload copying should be avoided as much as possible using references whenever possible. If the fan out is larger than one, the payload has to be cloned. In order to reduce copies even in that case, the cloned copies can be references of the same entities and only perform the actual copy if a downstream receiver has to modify its input. If it is not possible to avoid copying there are two possibilities: shallow copy (copy just the descriptor and share the data component) and deep copy (copy the data component as well maybe implementing copy-on-write).

The greatest disadvantage of the payload pattern compared to direct call is its inefficiency, associated with the message passing mechanism. One way to minimize it is by grouping different messages and sending them in a single package.

A consequence of this pattern is that new message types can be added without having to modify existing entities. If a component receives an unknown token, it just passes it downstream.